Evidence map›Paper›PMID 35333131›Full record

ArticleRadiology. Imaging cancer2022

Baseline CT-based Radiomic Features Aid Prediction of Nodal Positivity after Neoadjuvant Therapy in Pancreatic Cancer.

Sherif B Elsherif, Sanaz Javadi, Ott Le, Nathan Lamba, Matthew H G Katz, Eric P Tamm, Priya R Bhosale

Abstract read
In one paragraph

Article in Radiology. Imaging cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Sherif B ElsherifFrom the Departments of Diagnostic Radiology (S.B.E., S.J., O.L., E.P.T., P.R.B.) and Surgical Oncology (M.H.G.K.), The University of Texas MD Anderson Cancer Center, Houston, Tex; and MIM Software, Cleveland, Ohio (N.L.).ORCID 0000-0002-5964-7728
Sanaz JavadiFrom the Departments of Diagnostic Radiology (S.B.E., S.J., O.L., E.P.T., P.R.B.) and Surgical Oncology (M.H.G.K.), The University of Texas MD Anderson Cancer Center, Houston, Tex; and MIM Software, Cleveland, Ohio (N.L.).ORCID 0000-0003-2261-6757
Ott LeFrom the Departments of Diagnostic Radiology (S.B.E., S.J., O.L., E.P.T., P.R.B.) and Surgical Oncology (M.H.G.K.), The University of Texas MD Anderson Cancer Center, Houston, Tex; and MIM Software, Cleveland, Ohio (N.L.).
Nathan LambaFrom the Departments of Diagnostic Radiology (S.B.E., S.J., O.L., E.P.T., P.R.B.) and Surgical Oncology (M.H.G.K.), The University of Texas MD Anderson Cancer Center, Houston, Tex; and MIM Software, Cleveland, Ohio (N.L.).
Matthew H G KatzFrom the Departments of Diagnostic Radiology (S.B.E., S.J., O.L., E.P.T., P.R.B.) and Surgical Oncology (M.H.G.K.), The University of Texas MD Anderson Cancer Center, Houston, Tex; and MIM Software, Cleveland, Ohio (N.L.).
Eric P TammFrom the Departments of Diagnostic Radiology (S.B.E., S.J., O.L., E.P.T., P.R.B.) and Surgical Oncology (M.H.G.K.), The University of Texas MD Anderson Cancer Center, Houston, Tex; and MIM Software, Cleveland, Ohio (N.L.).
Priya R BhosaleFrom the Departments of Diagnostic Radiology (S.B.E., S.J., O.L., E.P.T., P.R.B.) and Surgical Oncology (M.H.G.K.), The University of Texas MD Anderson Cancer Center, Houston, Tex; and MIM Software, Cleveland, Ohio (N.L.).ORCID 0000-0003-4014-4941

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose To study the association between CT-derived textural features of pancreatic cancer and patient outcome. Materials and Methods This retrospective study evaluated 54 patients (median age, 62 years [range, 40-88 years]; 32 men) with pancreatic cancer who underwent chemoradiation followed by surgical resection and lymph node dissection from May 2012 to June 2016. Three-dimensional segmentation of the pancreatic tumor was performed on baseline dual-energy CT images: 70-keV pancreatic parenchymal phase (PPP) images and iodine material density images. Then, 15 and 19 radiomic features were extracted from each phase, respectively. Logistic regression with elastic net regularization was used to select textural features associated with outcome, and receiver operating characteristic analysis evaluated feature performance. Survival curves were generated using the Kaplan-Meier method. Results The feature of integral total (∫ T), representing the mean intensity in Hounsfield units times the contour volume in milliliters of PPP imaging (hereafter, "∫ T (HU·mL) (PPP)"), is inversely associated with posttherapy pathologic lymph node (ypN) category. A threshold ∫ T (HU·mL) (PPP) less than 507.85 predicted ypN1-2 classification with 96% sensitivity, 34% specificity, and area under the curve of 0.61. Patients with an ∫ T (HU·mL) (PPP) of less than 507.85 had decreased overall survival (median, 2.8 years) compared with patients with an ∫ T (HU·mL) (PPP) of 507.85 or greater (one event at 3.4 years) (

Indexed as

Neoadjuvant TherapyPancreatic NeoplasmsChemoradiotherapyHumansMaleMiddle AgedRetrospective StudiesTomography, X-Ray ComputedAbdomen/GICT–Dual EnergyOutcomes AnalysisPancreasTumor Response

Identifiers

PMID35333131
PMCPMC8965532

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.